A new key performance indicator oriented industrial process monitoring and operating performance assessment method based on improved Hessian locally linear embedding
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Publication:6099315
DOI10.1080/00207721.2022.2093420zbMath1518.93093MaRDI QIDQ6099315
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Publication date: 19 June 2023
Published in: International Journal of Systems Science (Search for Journal in Brave)
Kullback-Leibler divergenceHessian locally linear embeddingnonlinear process monitoringhot strip mill processindustrial operating performance assessment
Nonlinear systems in control theory (93C10) Control/observation systems involving computers (process control, etc.) (93C83)
Cites Work
- Unnamed Item
- Fault diagnosis of nonlinear and large-scale processes using novel modified kernel Fisher discriminant analysis approach
- Data-driven monitoring for stochastic systems and its application on batch process
- Recursive Filtering for Time-Varying Systems with Random Access Protocol
- Robust PLS approach for KPI-related prediction and diagnosis against outliers and missing data
- A novel graph-based partitioning algorithm for large-scale dynamical systems
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